MetaMath-Cybertron / README.md
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Adding Evaluation Results
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metadata
language:
  - en
license: apache-2.0
tags:
  - Math
datasets:
  - meta-math/MetaMathQA
pipeline_tag: text-generation
base_model:
  - fblgit/una-cybertron-7b-v2-bf16
  - meta-math/MetaMath-Mistral-7B
model-index:
  - name: MetaMath-Cybertron
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 66.47
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 85.54
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 63.71
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 57.71
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 79.64
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 70.51
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron
          name: Open LLM Leaderboard

MetaMath-Cybertron

Merge fblgit/una-cybertron-7b-v2-bf16 and meta-math/MetaMath-Mistral-7B using slerp merge.

You can use ChatML format.

Open LLM Leaderboard Evaluation Results

Detailed results can be found Coming soon

Metric Value
Avg. Coming soon
ARC (25-shot) Coming soon
HellaSwag (10-shot) Coming soon
MMLU (5-shot) Coming soon
TruthfulQA (0-shot) Coming soon
Winogrande (5-shot) Coming soon
GSM8K (5-shot) Coming soon

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 70.60
AI2 Reasoning Challenge (25-Shot) 66.47
HellaSwag (10-Shot) 85.54
MMLU (5-Shot) 63.71
TruthfulQA (0-shot) 57.71
Winogrande (5-shot) 79.64
GSM8k (5-shot) 70.51